scholarly journals Enhanced Magnetic Microwave Absorption at Low‐Frequency Band by Ferrite Assembled Microspheres with Controlled Components and Morphologies

2021 ◽  
Author(s):  
Mengqiu Huang ◽  
Xuefeng Yu ◽  
Lei Wang ◽  
Jiwei Liu ◽  
Wenbin You ◽  
...  
Keyword(s):  
Microwave Absorption ◽  
Frequency Band ◽  
Low Frequency

scholarly journals Facile synthesis and microwave absorption investigation of activated carbon@Fe3O4 composites in the low frequency band

RSC Advances ◽  
2018 ◽  
Vol 8 (41) ◽  
pp. 23048-23057 ◽  
Author(s):  
Pengfei Yin ◽  
Yu Deng ◽  
Limin Zhang ◽  
Ning Li ◽  
Xing Feng ◽  
...  
Keyword(s):  
Activated Carbon ◽  
Electromagnetic Wave ◽  
Hydrothermal Method ◽  
Microwave Absorption ◽  
Frequency Band ◽  
Low Frequency ◽  
Frequency Range ◽  
Facile Synthesis

Activated carbon@Fe3O4 composites with good electromagnetic wave absorbing performances in the low frequency range were synthesized via a hydrothermal method.

One‐Pot Hydrothermal Synthesis of Co 3 O 4 /MWCNTs/Graphene Composites with Enhanced Microwave Absorption in Low Frequency Band

ChemNanoMat ◽  
2019 ◽  
Vol 5 (6) ◽  
pp. 847-857 ◽  
Author(s):  
Yu Tao ◽  
Pengfei Yin ◽  
Limin Zhang ◽  
Xing Feng ◽  
Jian Wang ◽  
...  
Keyword(s):  
Hydrothermal Synthesis ◽  
Microwave Absorption ◽  
Frequency Band ◽  
Low Frequency ◽  
One Pot

Contact Current Density Analysis Inside Human Body in Low-Frequency Band Using Geometric Multi-Grid Solver

2020 ◽  
Vol E103.C (11) ◽  
pp. 588-596
Author(s):  
Masamune NOMURA ◽  
Yuki NAKAMURA ◽  
Hiroo TARAO ◽  
Amane TAKEI
Keyword(s):  
Frequency Band ◽  
Current Density ◽  
Human Body ◽  
Low Frequency ◽  
Density Analysis

Low-frequency microwave absorption of MOF-derived Co/CoO/SrCO3@C composites

2021 ◽  
pp. 124457
Author(s):  
Limin Zhang ◽  
Pengfei Yin ◽  
Jian Wang ◽  
Xing Feng ◽  
Jianwu Dai
Keyword(s):  
Microwave Absorption ◽  
Low Frequency

scholarly journals Spillovers of Stock Markets among the BRICS: New Evidence in Time and Frequency Domains before the Outbreak of COVID-19 Pandemic

2021 ◽  
Vol 14 (3) ◽  
pp. 112
Author(s):  
Kai Shi
Keyword(s):  
Stock Market ◽  
Frequency Band ◽  
Stock Markets ◽  
Emerging Market ◽  
Low Frequency ◽  
Systematic Risk ◽  
Error Variance ◽  
Frequency Bands ◽  
Volatility Spillovers ◽  
Risk Sources

We attempted to comprehensively decode the connectedness among the abbreviation of five emerging market countries (BRICS) stock markets between 1 August 2002 and 31 December 2019 not only in time domain but also in frequency domain. A continuously varying spillover index based on forecasting error variance decomposition within a generalized abbreviation of vector-autoregression (VAR) framework was computed. With the help of spectral representation, heterogeneous frequency responses to shocks were separated into frequency-specific spillovers in five different frequency bands to reveal differentiated linkages among BRICS markets. Rolling sample analyses were introduced to allow for multiple changes during the sample period. It is found that return spillovers dominated by the high frequency band (within 1 week) part declined with the drop of frequencies, while volatility spillovers dominated by the low frequency band (above 1 quarter) part grew with the decline in frequencies; the dynamics of spillovers were influenced by crucial systematic risk events, and some similarities implied in the spillover dynamics in different frequency bands were found. From the perspective of identifying systematic risk sources, China’s stock market and Russia’s stock market, respectively, played an influential role for return spillover and volatility spillover across BRICS markets.

Locally resonant periodic structures with low-frequency band gaps

2013 ◽  
Vol 114 (3) ◽  
pp. 033532 ◽  
Author(s):  
Zhibao Cheng ◽  
Zhifei Shi ◽  
Y. L. Mo ◽  
Hongjun Xiang
Keyword(s):  
Frequency Band ◽  
Periodic Structures ◽  
Low Frequency ◽  
Band Gaps

An Effective Brain Imaging Biomarker for AD and aMCI: ALFF in Slow-5 Frequency Band

2021 ◽  
Vol 18 ◽  
Author(s):  
Luoyu Wang ◽  
Qi Feng ◽  
Mei Wang ◽  
Tingting Zhu ◽  
Enyan Yu ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Frequency Band ◽  
Low Frequency ◽  
Posterior Cingulate Cortex ◽  
Angular Gyrus ◽  
Imaging Biomarker ◽  
Support Vector ◽  
Frequency Bands ◽  
Local Functional ◽  
Left Angular Gyrus

Background: As a potential brain imaging biomarker, amplitude of low frequency fluc-tuation (ALFF) has been used as a feature to distinguish patients with Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI) from normal controls (NC). However, it remains unclear whether the frequency-dependent pattern of ALFF alterations can effectively distinguish the different phases of the disease. Methods: In the present study, 52 AD and 50 aMCI patients were enrolled together with 43 NC in total. The ALFF values were calculated in the following three frequency bands: classical (0.01-0.08 Hz), slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) for the three different groups. Subsequently, the local functional abnormalities were employed as features to examine the effect of classification among AD, aMCI and NC using a support vector machine (SVM). Results: We found that the among-group differences of ALFF in the different frequency bands were mainly located in the left hippocampus (HP), right HP, bilateral posterior cingulate cortex (PCC) and bilateral precuneus (PCu), left angular gyrus (AG) and left medial prefrontal cortex (mPFC). When the local functional abnormalities were employed as features, we identified that the ALFF in the slow-5 frequency band showed the highest accuracy to distinguish among the three groups. Conclusion: These findings may deepen our understanding of the pathogenesis of AD and suggest that slow-5 frequency band may be helpful to explore the pathogenesis and distinguish the phases of this disease.

Sign in / Sign up

Export Citation Format

Share Document